Senior AI/ML Audio Engineer (f/m/d)

In this role, you will design, implement, optimize, and validate advanced audio processing on NXP’s automotive AI platforms. You will work at the intersection of AI/ML and signal processing to deliver embedded audio solutions for future cars and robotics. You will collaborate with cross-functional teams to translate requirements into efficient software and hardware-friendly implementations. Your work will focus on improving audio experiences while managing latency, power, and footprint on resource-constrained hardware. This is an opportunity to shape cutting-edge in-vehicle audio technology within a collaborative, automotive-focused team in Dresden.

• Design, implement, optimize and validate advanced audio processing solutions on AI-enabled automotive/robotics platforms
• Develop and adapt AI/ML models for embedded audio systems
• Implement software in C/C++ and Python with a focus on efficiency and validation
• Manage model optimization, quantization, and memory footprint reduction for constrained hardware
• Assess and improve DSP/NPUs interaction with AI/ML approaches
• Analyze system-level requirements and translate them into robust software implementations
• Collaborate with cross-functional teams to deliver audio solutions for automotive applications

• Strong foundation in AI/ML, signal processing, and audio algorithms
• Experience with PyTorch, TensorFlow or equivalent frameworks
• Solid background in audio processing techniques (noise reduction, echo cancellation, beamforming, speech enhancement)
• Embedded AI deployment experience including optimization and quantization
• Proficiency in C/C++ and Python for algorithm implementation
• Understanding of DSP/NPUs and their interaction with AI approaches
• Familiarity with performance metrics (latency, throughput, memory, power)
• Knowledge of automotive standards (IATF16949, ISO26262) is a plus
• 3+ years in automotive/robotics audio systems or edge AI; MSc/PhD preferred

• Teamwork and collaboration
• Analytical thinking
• Problem-solving orientation
• AI/ML model development for embedded systems
• Model optimization and quantization for edge deployment
• Audio signal processing (noise reduction, echo cancellation, beamforming)